66,147 research outputs found
Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking
Light Detection and Ranging (LIDAR) sensors play an important role in the
perception stack of autonomous robots, supplying mapping and localization
pipelines with depth measurements of the environment. While their accuracy
outperforms other types of depth sensors, such as stereo or time-of-flight
cameras, the accurate modeling of LIDAR sensors requires laborious manual
calibration that typically does not take into account the interaction of laser
light with different surface types, incidence angles and other phenomena that
significantly influence measurements. In this work, we introduce a physically
plausible model of a 2D continuous-wave LIDAR that accounts for the
surface-light interactions and simulates the measurement process in the Hokuyo
URG-04LX LIDAR. Through automatic differentiation, we employ gradient-based
optimization to estimate model parameters from real sensor measurements.Comment: Published at ICRA 202
TiEV: The Tongji Intelligent Electric Vehicle in the Intelligent Vehicle Future Challenge of China
TiEV is an autonomous driving platform implemented by Tongji University of
China. The vehicle is drive-by-wire and is fully powered by electricity. We
devised the software system of TiEV from scratch, which is capable of driving
the vehicle autonomously in urban paths as well as on fast express roads. We
describe our whole system, especially novel modules of probabilistic perception
fusion, incremental mapping, the 1st and the 2nd planning and the overall
safety concern. TiEV finished 2016 and 2017 Intelligent Vehicle Future
Challenge of China held at Changshu. We show our experiences on the development
of autonomous vehicles and future trends
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Evaluation of laser range-finder mapping for agricultural spraying vehicles
In this paper, we present a new application of laser range-finder sensing to agricultural spraying vehicles. The current generation of spraying vehicles use automatic controllers to maintain the height of the sprayer booms above the crop.
However, these control systems are typically based on ultrasonic sensors mounted on the booms, which limits the accuracy of the measurements and the response of the controller to changes in the terrain, resulting in a sub-optimal spraying process. To overcome these limitations, we propose to use a laser scanner, attached to the front of the sprayer's cabin, to scan the ground surface in front of the vehicle and to build a scrolling 3d map of the terrain. We evaluate the proposed solution in a series of field tests, demonstrating that the approach provides a more detailed and accurate representation of the environment than the current sonar-based solution, and which can lead to the development of more efficient boom control systems
Conceptual spatial representations for indoor mobile robots
We present an approach for creating conceptual representations of human-made indoor environments using mobile
robots. The concepts refer to spatial and functional properties of typical indoor environments. Following ļ¬ndings
in cognitive psychology, our model is composed of layers representing maps at diļ¬erent levels of abstraction. The
complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition.
The system also incorporates a linguistic framework that actively supports the map acquisition process, and which
is used for situated dialogue. Finally, we discuss the capabilities of the integrated system
OPEN SOURCE WEB TOOL FOR TRACKING IN A LOWCOST MOBILE MAPPING SYSTEM
During the last decade several Mobile Mapping Systems (MMSs), i.e. systems able to acquire efficiently three dimensional data using
moving sensors (Guarnieri et al., 2008, Schwarz and El-Sheimy, 2004), have been developed. Research and commercial products have
been implemented on terrestrial, aerial and marine platforms, and even on human-carried equipment, e.g. backpack (Lo et al., 2015,
Nex and Remondino, 2014, Ellum and El-Sheimy, 2002, Leica Pegasus backpack, 2016, Masiero et al., 2017, Fissore et al., 2018).<br><br>
Such systems are composed of an integrated array of time-synchronised navigation sensors and imaging sensors mounted on a mobile
platform (Puente et al., 2013, Tao and Li, 2007). Usually the MMS implies integration of different types of sensors, such as GNSS,
IMU, video camera and/or laser scanners that allow accurate and quick mapping (Li, 1997, Petrie, 2010, Tao, 2000). The typical
requirement of high-accuracy 3D georeferenced reconstruction often makes such systems quite expensive. Indeed, at time of writing
most of the terrestrial MMSs on the market have a cost usually greater than 50000, which might be expensive for certain applications
(Ellum and El-Sheimy, 2002, Piras et al., 2008). In order to allow best performance sensors have to be properly calibrated (Dong et
al., 2007, Ellum and El-Sheimy, 2002).<br><br>
Sensors in MMSs are usually integrated and managed through a dedicated software, which is developed ad hoc for the devices mounted
on the mobile platform and hence tailored for the specific used sensors. Despite the fact that commercial solutions are complete, very
specific and particularly related to the typology of survey, their price is a factor that restricts the number of users and the possible
interested sectors.<br><br>
This paper describes a (relatively low cost) terrestrial Mobile Mapping System developed at the University of Padua (TESAF, Department
of Land Environment Agriculture and Forestry) by the research team in CIRGEO, in order to test an alternative solution to other
more expensive MMSs. The first objective of this paper is to report on the development of a prototype of MMS for the collection of
geospatial data based on the assembly of low cost sensors managed through a web interface developed using open source libraries. The
main goal is to provide a system accessible by any type of user, and flexible to any type of upgrade or introduction of new models of
sensors or versions thereof. After a presentation of the hardware components used in our system, a more detailed description of the
software developed for the management of the MMS will be provided, which is the part of the innovation of the project. According to
the worldwide request for having big data available through the web from everywhere in the world (Pirotti et al., 2011), the proposed
solution allows to retrieve data from a web interface Figure 4. Actually, this is part of a project for the development of a new web
infrastructure in the University of Padua (but it will be available for external users as well), in order to ease collaboration between
researchers from different areas.<br><br>
Finally, strengths, weaknesses and future developments of the low cost MMS are discussed
COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELS
This paper considers Leica backpack and photogrammetric surveys of a mediaeval bastion in Padua, Italy. Furhtermore, terrestrial
laser scanning (TLS) survey is considered in order to provide a state of the art reconstruction of the bastion. Despite control points
are typically used to avoid deformations in photogrammetric surveys and ensure correct scaling of the reconstruction, in this paper
a different approach is considered: this work is part of a project aiming at the development of a system exploiting ultra-wide band
(UWB) devices to provide correct scaling of the reconstruction. In particular, low cost Pozyx UWB devices are used to estimate
camera positions during image acquisitions. Then, in order to obtain a metric reconstruction, scale factor in the photogrammetric
survey is estimated by comparing camera positions obtained from UWB measurements with those obtained from photogrammetric
reconstruction. Compared with the TLS survey, the considered photogrammetric model of the bastion results in a RMSE of 21.9cm, average error 13.4cm, and standard deviation 13.5cm. Excluding the final part of the bastion left wing, where the presence of several poles make reconstruction more difficult, (RMSE) fitting error is 17.3cm, average error 11.5cm, and standard deviation 9.5cm. Instead, comparison of Leica backpack and TLS surveys leads to an average error of 4.7cm and standard deviation 0.6cm (4.2 cm and 0.3 cm, respectively, by excluding the final part of the left wing)
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